Energy efficient engine, high pressure turbine thermal barrier coating. Support technology report

This report describes the work performed on a thermal barrier coating support technology task of the Energy Efficient Engine Component Development Program. A thermal barrier coating (TBC) system consisting of a Ni-Cr-Al-Y bond cost layer and ZrO2-Y2O3 ceramic layer was selected from eight candidate coating systems on the basis of laboratory tests. The selection was based on coating microstructure, crystallographic phase composition, tensile bond and bend test results, erosion and impact test results, furnace exposure, thermal cycle, and high velocity dynamic oxidation test results. Procedures were developed for applying the selected TBC to CF6-50, high pressure turbine blades and vanes. Coated HPT components were tested in three kinds of tests. Stage 1 blades were tested in a cascade cyclic test rig, Stage 2 blades were component high cycle fatigue tested to qualify thermal barrier coated blades for engine testing, and Stage 2 blades and Stage 1 and 2 vanes were run in factory engine tests. After completion of the 1000 cycle engine test, the TBC on the blades was in excellent condition over all of the platform and airfoil except at the leading edge above midspan on the suction side of the airfoil. The coating damage appeared to be caused by particle impingement; adjacent blades without TBC also showed evidence of particle impingement

Euler/Navier-Stokes calculations of transonic flow past fixed- and rotary-wing aircraft configurations

Computational fluid dynamics has an increasingly important role in the design and analysis of aircraft as computer hardware becomes faster and algorithms become more efficient. Progress is being made in two directions: more complex and realistic configurations are being treated and algorithms based on higher approximations to the complete Navier-Stokes equations are being developed. The literature indicates that linear panel methods can model detailed, realistic aircraft geometries in flow regimes where this approximation is valid. As algorithms including higher approximations to the Navier-Stokes equations are developed, computer resource requirements increase rapidly. Generation of suitable grids become more difficult and the number of grid points required to resolve flow features of interest increases. Recently, the development of large vector computers has enabled researchers to attempt more complex geometries with Euler and Navier-Stokes algorithms. The results of calculations for transonic flow about a typical transport and fighter wing-body configuration using thin layer Navier-Stokes equations are described along with flow about helicopter rotor blades using both Euler/Navier-Stokes equations

Generation of Symmetric Dicke States of Remote Qubits with Linear Optics

We propose a method for generating all symmetric Dicke states, either in the long-lived internal levels of N massive particles or in the polarization degrees of freedom of photonic qubits, using linear optical tools only. By means of a suitable multiphoton detection technique, erasing Welcher-Weg information, our proposed scheme allows the generation and measurement of an important class of entangled multiqubit states.Comment: New version, a few modifications and a new figure, accepted in Physical Review Letter

Signatures of the Pair-Coherent State

We explore in detail the possibility of generating a pair-coherent state in the non-degenerate parametric oscillator when decoherence is included. Such states are predicted in the transient regime in parametric oscillation where the pump mode is adiabatically eliminated. Two specific signatures are examined to indicate whether the state of interest has been generated, the Schrodinger cat state - like signatures, and the fidelity. Solutions in a transient regime reveal interference fringes which are indicative of the formation of a Schrodinger cat state. The fidelity indicates the purity of our prepared state compared to the ideal pair-coherent state.Comment: Figures hacked down to size for serve

The Computational Power of Optimization in Online Learning

We consider the fundamental problem of prediction with expert advice where the experts are "optimizable": there is a black-box optimization oracle that can be used to compute, in constant time, the leading expert in retrospect at any point in time. In this setting, we give a novel online algorithm that attains vanishing regret with respect to $N$ experts in total $\widetilde{O}(\sqrt{N})$ computation time. We also give a lower bound showing that this running time cannot be improved (up to log factors) in the oracle model, thereby exhibiting a quadratic speedup as compared to the standard, oracle-free setting where the required time for vanishing regret is $\widetilde{\Theta}(N)$. These results demonstrate an exponential gap between the power of optimization in online learning and its power in statistical learning: in the latter, an optimization oracle---i.e., an efficient empirical risk minimizer---allows to learn a finite hypothesis class of size $N$ in time $O(\log{N})$. We also study the implications of our results to learning in repeated zero-sum games, in a setting where the players have access to oracles that compute, in constant time, their best-response to any mixed strategy of their opponent. We show that the runtime required for approximating the minimax value of the game in this setting is $\widetilde{\Theta}(\sqrt{N})$, yielding again a quadratic improvement upon the oracle-free setting, where $\widetilde{\Theta}(N)$ is known to be tight